R Notebook

#pacman::p_install_gh("systats/binoculaR")
pacman::p_load(tidyverse, haven, magrittr, car, psych, binoculaR)

Load in Data

arab4 <- read_spss("data/arab4.sav")
arab3 <- read_spss("data/arab3.sav")
# arab4 <- get(load(url("https://github.com/favstats/GodlyGovernance/raw/master/data/arab4.Rdata")))

Inspect Data

#b_select <- binoculaR::binoculaR(arab4)
#dput(b_select$var_codes)
#index <- c("country","wt" ,"sample" ,"a1", "q1", "q2", "q13", "q5182", 
#"q5184", "q6013", "q6014", "q6018", "q60118", "q605a", "q6061", "q6062", 
#"q6063", "q6064", "q6071", "q6074", "q6076", "q707", "q708", 
#"q7114", "q1001", "q1002", "q1003", "t1003", "q1004", "q1005", 
#"q609", "q6101", "q6106", "q1012", "q1012a", "q1016")
#
#arab4 %<>%
#  select(index)
#
#arab4
#view_df2(arab3, hide.progress = T)
# save(arab4, file = "data/arab4.Rdata")

Filter Data

arab4 %<>%
  filter(q1012 == 1) %>%#only Muslims
  mutate(sample = ifelse(is.na(sample) | sample == 1, 1, 2)) %>% 
  filter(sample != 2) #only non-refugees
arab3 %<>%
  filter(q1012 == 1) #only Muslims
arab3

arab4

Recode Data

Arab3

arab3 %<>% 
  mutate(cntry = sjmisc::to_label(country)) %>% 
  mutate(region = sjmisc::to_label(a1)) %>% 
  mutate(governorate = sjmisc::to_label(q1)) %>% 
  mutate(year = lubridate::year(date))
  # Dependent Variable
arab3 %<>% 
  mutate(islamistparties1 = ifelse(q518a2 > 5, NA, 5 - q518a2)) %>%
  mutate(islamistparties2 = ifelse(q518b2 > 5, NA, 5 - q518b2)) %>% 
  mutate(islamistparties = case_when(
        islamistparties1 == 1 ~ 1,
        islamistparties1 == 2 ~ 2,
        islamistparties1 == 3 ~ 3,
        islamistparties1 == 4 ~ 4,
        islamistparties2 == 1 ~ 1,
        islamistparties2 == 2 ~ 2,
        islamistparties2 == 3 ~ 3,
        islamistparties2 == 4 ~ 4)
    ) %>%  
  mutate(islamistgov = ifelse(q5184 > 5, NA, 5 - q5184)) %>% 
  mutate(religinterfere = ifelse(q6061 > 5, NA, q6061)) %>% 
  mutate(religleaders = ifelse(q6062 > 5, NA, 5 - q6062)) %>% 
  mutate(religleadersinfl = ifelse(q6063 > 5, NA, 5 - q6063)) %>%
  mutate(seperation = ifelse(q6064 > 5, NA, q6064)) %>% 
  mutate(religparty = Recode(q605a, "1 = 1;
                                     2 = 1;
                                     3 = 0;
                                     4 = 0;
                                     5 = 0;
                                    8 = 0;
                                    9 = NA")) %>% 
  mutate(religparty2 = Recode(q605a, "1 = 5;
                                      2 = 4;
                                      3 = 2;
                                      4 = 1;
                                      5 = 3;
                                     8 = NA;
                                     9 = NA"))
ifelse4cat_rec <- function(variable) {
  recoded <- ifelse(variable == 0 | variable > 5, NA, 5 - variable)
  return(recoded)
}
arab3 %<>% 
  mutate(female = ifelse(sex == 2, 1, 0)) %>% 
  mutate(work = ifelse(q1004 == 0 | q1004 > 5, NA, abs(q1004 - 2))) %>% 
  mutate(income = ifelse4cat_rec(q1016)) %>% 
  mutate(age = ifelse(q1001 == 0 | q1001 == 9999, NA, q1001)) %>% 
  mutate(educ = case_when(
        q1003 == 0 ~ NA_real_,
        q1003 == 99 ~ NA_real_,
        q1003 == 5 ~ 4,
        q1003 == 6 ~ 5,
        q1003 == 7 ~ 6,
        q1003yem == 0 ~ NA_real_,
        q1003yem == 99 ~ NA_real_,
        q1003yem == 4 ~ 3,
        q1003yem == 5 ~ 4,
        q1003yem == 6 ~ 5,
        q1003yem == 7 ~ 5,
        q1003yem == 8 ~ 6,
        q1003t == 0 ~ NA_real_,
        q1003t == 99 ~ NA_real_,
        q1003t == 1 ~ 1,
        q1003t == 2 ~ 2,
        q1003t == 3 ~ 3,
        q1003t == 4 ~ 4,
        q1003t == 5 ~ 5,
        q1003t == 6 ~ 6,
    TRUE ~ as.numeric(q1003))
    ) %>% 
  mutate(globalism = ifelse(q701b == 0 | q701b > 5, NA, q701b)) %>% 
  mutate(pray = ifelse(q6101 == 0 | q6101 > 5, NA, 6 - q6101)) %>% 
  mutate(quran = ifelse(q6106 == 0 | q6106 > 5, NA, 6 - q6106)) %>%
  mutate(womanwork = ifelse(q6012 == 0 | q6012 > 5, NA, q6012)) %>% 
  mutate(womenleader = ifelse4cat_rec(q6013)) %>% 
  mutate(womeneduc = ifelse4cat_rec(q6014)) %>% 
  mutate(nodemoc = ifelse(q6071 == 0 | q6071 > 5, NA, q6071)) %>% 
  mutate(genderapartuni = ifelse4cat_rec(q6074)) %>% 
  mutate(coverup = ifelse4cat_rec(q6076)) %>% 
  select(cntry, year, region, governorate, islamistparties , islamistgov, religinterfere, religleaders, religleadersinfl, seperation, religparty, religparty2, female, work, income,  age, educ, globalism, pray, quran, womanwork, womenleader, womeneduc, nodemoc, genderapartuni, coverup)

Arab4

table(arab4$country)

   1    5    8   10   13   15   21 
1199 1146 1172  615 1199 1177 1200 

arab4 %<>% 
  mutate(cntry = sjmisc::to_label(country)) %>% 
  mutate(region = sjmisc::to_label(a1)) %>% 
  mutate(governorate = sjmisc::to_label(q1)) %>% 
  mutate(year = 2016)#%>%
#  mutate(district = sjmisc::to_label(q2)) 
# Dependent Variable
arab4 %<>% 
  mutate(islamistparties = ifelse(q5182 > 5, NA, 5 - q5182)) %>% 
  mutate(islamistgov = ifelse(q5184 > 5, NA, 5 - q5184)) %>% 
  mutate(religinterfere = ifelse(q6061 > 5, NA, q6061)) %>% 
  mutate(religleaders = ifelse(q6062 > 5, NA, 5 - q6062)) %>% 
  mutate(religleadersinfl = ifelse(q6063 > 5, NA, 5 - q6063)) %>%
  mutate(seperation = ifelse(q6064 > 5, NA, q6064)) %>% 
  mutate(religparty = Recode(q605a, "1 = 1;
                                     2 = 1;
                                     3 = 0;
                                     4 = 0;
                                     5 = 0;
                                    98 = 0;
                                    99 = NA")) %>% 
  mutate(religparty2 = Recode(q605a, "1 = 5;
                                      2 = 4;
                                      3 = 2;
                                      4 = 1;
                                      5 = 3;
                                     98 = NA;
                                     99 = NA"))
arab4 %<>% 
  mutate(female = ifelse(q1002 == 2, 1, 0)) %>% 
  mutate(work = ifelse(q1004 == 0 | q1004 > 5, NA, abs(q1004 - 2))) %>% 
  mutate(income = ifelse4cat_rec(q1016)) %>% 
  mutate(age = ifelse(q1001 == 0 | q1001 == 9999, NA, q1001)) %>% 
  mutate(educ = case_when(
        q1003 == 0 ~ NA_real_,
        q1003 == 98 ~ NA_real_,
        q1003 == 99 ~ NA_real_,
        q1003 == 5 ~ 4,
        q1003 == 6 ~ 5,
        q1003 == 7 ~ 6,
        t1003 == 0 ~ NA_real_,
        t1003 == 98 ~ NA_real_,
        t1003 == 99 ~ NA_real_,
        t1003 == 3 ~ 3,
        t1003 == 4 ~ 4,
        t1003 == 5 ~ 5,
        t1003 == 6 ~ 6,
    TRUE ~ as.numeric(q1003))
    ) %>% 
  mutate(globalism = ifelse(q701b == 0 | q701b > 5, NA, q701b)) %>% 
  mutate(pray = ifelse(q6101 == 0 | q6101 > 5, NA, 6 - q6101)) %>% 
  mutate(quran = ifelse(q6106 == 0 | q6106 > 5, NA, 6 - q6106)) %>% 
  mutate(womanwork = ifelse(q6012 == 0 | q6012 > 5, NA, q6012)) %>% 
  mutate(womenleader = ifelse4cat_rec(q6013)) %>% 
  mutate(womeneduc = ifelse4cat_rec(q6014)) %>% 
  mutate(nodemoc = ifelse(q6071 == 0 | q6071 > 5, NA, q6071)) %>% 
  mutate(genderapartuni = ifelse4cat_rec(q6074)) %>% 
  mutate(coverup = ifelse4cat_rec(q6076)) %>% 
  select(cntry, year, region, governorate , islamistparties , islamistgov, religinterfere, religleaders, religleadersinfl, seperation, religparty, religparty2, female, work, income,  age, educ, globalism, pray, quran, womanwork, womenleader, womeneduc, nodemoc, genderapartuni, coverup)

Merging

arab3;arab4

arab <- rbind(arab4,arab3)
arab

table(arab$year)

2012 2013 2014 2016 
 835 8901 2352 7708 

table(arab$cntry)

  Algeria     Egypt    Jordan   Lebanon   Morocco 
     2419      2273      2957      1345      2314 
Palestine     Qatar   Tunisia      Iraq    Kuwait 
     2346         0      2399      1213      1018 
    Libya     Sudan     Yemen 
     1235      1198      1198 

Factor Analysis

f31 <- arab %>% 
  select(islamistparties, islamistgov, 
         religleaders, religleadersinfl) %>% 
  fa(1, rotate = "promax",   
        fm = "pa",
        scores = "regression")           
fa.diagram(f31)                                  

f31              

Factor Analysis using method =  pa
Call: fa(r = ., nfactors = 1, rotate = "promax", scores = "regression", 
    fm = "pa")
Standardized loadings (pattern matrix) based upon correlation matrix
                  PA1   h2   u2 com
islamistparties  0.55 0.30 0.70   1
islamistgov      0.54 0.29 0.71   1
religleaders     0.71 0.50 0.50   1
religleadersinfl 0.63 0.40 0.60   1

                PA1
SS loadings    1.50
Proportion Var 0.38

Mean item complexity =  1
Test of the hypothesis that 1 factor is sufficient.

The degrees of freedom for the null model are  6  and the objective function was  0.75 with Chi Square of  16491.97
The degrees of freedom for the model are 2  and the objective function was  0.09 

The root mean square of the residuals (RMSR) is  0.08 
The df corrected root mean square of the residuals is  0.14 

The harmonic number of observations is  19654 with the empirical chi square  1517.15  with prob <  0 
The total number of observations was  21915  with Likelihood Chi Square =  1941.79  with prob <  0 

Tucker Lewis Index of factoring reliability =  0.647
RMSEA index =  0.21  and the 90 % confidence intervals are  0.203 0.218
BIC =  1921.8
Fit based upon off diagonal values = 0.96
Measures of factor score adequacy             
                                                   PA1
Correlation of (regression) scores with factors   0.85
Multiple R square of scores with factors          0.72
Minimum correlation of possible factor scores     0.43

arab %>% 
  select(islamistparties, islamistgov, 
         religleaders, religleadersinfl) %>% 
  alpha() 

Reliability analysis   
Call: alpha(x = .)

  raw_alpha std.alpha G6(smc) average_r S/N    ase mean
       0.7       0.7    0.66      0.37 2.3 0.0034    2
   sd
 0.71

 lower alpha upper     95% confidence boundaries
0.69 0.7 0.71 

 Reliability if an item is dropped:
                 raw_alpha std.alpha G6(smc) average_r S/N
islamistparties       0.65      0.65    0.58      0.39 1.9
islamistgov           0.65      0.66    0.58      0.39 1.9
religleaders          0.60      0.60    0.51      0.33 1.5
religleadersinfl      0.64      0.64    0.54      0.37 1.7
                 alpha se
islamistparties    0.0042
islamistgov        0.0041
religleaders       0.0046
religleadersinfl   0.0042

 Item statistics 
                     n raw.r std.r r.cor r.drop mean   sd
islamistparties  20198  0.72  0.71  0.55   0.46  1.7 0.95
islamistgov      20135  0.73  0.71  0.54   0.46  1.7 1.02
religleaders     20431  0.75  0.76  0.66   0.53  2.3 0.92
religleadersinfl 20524  0.72  0.73  0.60   0.48  2.2 0.89

Non missing response frequency for each item
                    1    2    3    4 5 miss
islamistparties  0.59 0.19 0.15 0.07 0 0.08
islamistgov      0.59 0.17 0.14 0.10 0 0.08
religleaders     0.21 0.38 0.31 0.10 0 0.07
religleadersinfl 0.24 0.42 0.26 0.08 0 0.06

arab %>% 
  select(islamistparties, islamistgov, 
         religleaders, religleadersinfl) %>% 
  KMO() 

Kaiser-Meyer-Olkin factor adequacy
Call: KMO(r = .)
Overall MSA =  0.68
MSA for each item = 
 islamistparties      islamistgov     religleaders 
            0.71             0.72             0.66 
religleadersinfl 
            0.66 

arab4 %>% 
  select(islamistparties, islamistgov, 
         religleaders, religleadersinfl,
         religparty2, seperation,
         religinterfere) %>% 
  na.omit() %>% 
  cor()  

                 islamistparties islamistgov religleaders
islamistparties        1.0000000   0.3760955    0.3274069
islamistgov            0.3760955   1.0000000    0.3180997
religleaders           0.3274069   0.3180997    1.0000000
religleadersinfl       0.2595854   0.3059820    0.5628358
religparty2            0.2625742   0.2409189    0.3812004
seperation             0.1409401   0.2186956    0.3190967
religinterfere         0.1393481   0.1283822    0.2070613
                 religleadersinfl religparty2 seperation
islamistparties         0.2595854   0.2625742  0.1409401
islamistgov             0.3059820   0.2409189  0.2186956
religleaders            0.5628358   0.3812004  0.3190967
religleadersinfl        1.0000000   0.3120300  0.2944263
religparty2             0.3120300   1.0000000  0.2819491
seperation              0.2944263   0.2819491  1.0000000
religinterfere          0.2539891   0.1671423  0.2725233
                 religinterfere
islamistparties       0.1393481
islamistgov           0.1283822
religleaders          0.2070613
religleadersinfl      0.2539891
religparty2           0.1671423
seperation            0.2725233
religinterfere        1.0000000

arab <- predict(f31, arab %>% 
  select(islamistparties, islamistgov, 
         religleaders, religleadersinfl)) %>% 
  data.frame() %>% 
  cbind(arab) %>% 
  mutate(islamism = PA1) #%>% 
#  ggplot(aes(islamism)) +
#  geom_histogram() +
#  facet_wrap(~cntry, scales = "free")
#sjPlot::view_df(arab, show.frq = T, show.prc = T)

Creating indices

Regression

vif.mer(model2)

                    female                       work 
                  1.313155                   1.270084 
                    income                        age 
                  1.062632                   1.074094 
                      educ                  globalism 
                  1.155690                   1.052950 
             personalpiety          patriarchalvalues 
                  1.076342                   1.162692 
              liberalislam personalpiety:liberalislam 
                  1.109287                   1.026315 

model1 <- arab %>% 
  lme4::lmer(islamism ~ female + work + income + age + educ + globalism + pray + quran + womanwork + womenleader + womeneduc + nodemoc + genderapartuni + coverup + (1|cntry/year), data = .)

texreg::screenreg(model1)

plot_model(model1, sort.est = T, show.values = T, show.p = T, value.offset = 0.5)


plot_model(model1, terms = c("nodemoc", "female"), type = "pred")

model2 <- arab %>% 
  lme4::lmer(islamism ~ female + work + income + age + educ + globalism + pray + quran + womanwork + womenleader + womeneduc + nodemoc + genderapartuni + coverup + nodemoc*quran + (1|cntry/year), data = .)

texreg::screenreg(model2)

view_df2 <- function (x, weight.by = NULL, altr.row.col = TRUE, show.id = TRUE, 
  show.type = FALSE, show.values = TRUE, show.string.values = FALSE, 
  show.labels = TRUE, show.frq = FALSE, show.prc = FALSE, 
  show.wtd.frq = FALSE, show.wtd.prc = FALSE, show.na = FALSE, 
  max.len = 15, sort.by.name = FALSE, wrap.labels = 50, hide.progress = FALSE, 
  CSS = NULL, encoding = NULL, file = NULL, use.viewer = TRUE, 
  no.output = FALSE, remove.spaces = TRUE) 
{
  get.encoding <- function(encoding, data = NULL) {
  if (is.null(encoding)) {
    if (!is.null(data) && is.data.frame(data)) {
      # get variable label
      labs <- sjlabelled::get_label(data[[1]])
      # check if vectors of data frame have
      # any valid label. else, default to utf-8
      if (!is.null(labs) && is.character(labs))
        encoding <- Encoding(sjlabelled::get_label(data[[1]]))
      else
        encoding <- "UTF-8"
      # unknown encoding? default to utf-8
      if (encoding == "unknown") encoding <- "UTF-8"
    } else if (.Platform$OS.type == "unix")
      encoding <- "UTF-8"
    else
      encoding <- "Windows-1252"
  }
  return(encoding)
}

  has_value_labels <- function(x) {
  !(is.null(attr(x, "labels", exact = T)) && is.null(attr(x, "value.labels", exact = T)))
}

  sju.rmspc <- function(html.table) {
  cleaned <- gsub("      <", "<", html.table, fixed = TRUE, useBytes = TRUE)
  cleaned <- gsub("    <", "<", cleaned, fixed = TRUE, useBytes = TRUE)
  cleaned <- gsub("  <", "<", cleaned, fixed = TRUE, useBytes = TRUE)
  return(cleaned)
  }
  
  frq.value <- function(index, x, df.val, weights = NULL) {
  valstring <- ""
  # check if we have a valid index
  if (index <= ncol(x) && !is.null(df.val[[index]])) {
    # do we have weights?
    if (!is.null(weights))
      variab <- sjstats::weight(x[[index]], weights)
    else
      variab <- x[[index]]
    # create frequency table. same function as for
    # sjt.frq and sjp.frq
    ftab <- create.frq.df(variab, 20)$mydat$frq
    # remove last value, which is N for NA
    if (length(ftab) == 1 && is.na(ftab)) {
      valstring <- "<NA>"
    } else {
      for (i in 1:(length(ftab) - 1)) {
        valstring <- paste0(valstring, ftab[i])
        if (i < length(ftab)) valstring <- paste0(valstring, "<br>")
      }
    }
  } else {
    valstring <- ""
  }
  return(valstring)
}

prc.value <- function(index, x, df.val, weights = NULL) {
  valstring <- ""
  # check for valid indices
  if (index <= ncol(x) && !is.null(df.val[[index]])) {
    # do we have weights?
    if (!is.null(weights))
      variab <- sjstats::weight(x[[index]], weights)
    else
      variab <- x[[index]]
    # create frequency table, but only get valid percentages
    ftab <- create.frq.df(variab, 20)$mydat$valid.prc
    # remove last value, which is a NA dummy
    if (length(ftab) == 1 && is.na(ftab)) {
      valstring <- "<NA>"
    } else {
      for (i in 1:(length(ftab) - 1)) {
        valstring <- paste0(valstring, sprintf("%.2f", ftab[i]))
        if (i < length(ftab)) valstring <- paste0(valstring, "<br>")
      }
    }
  } else {
    valstring <- ""
  }
  return(valstring)
}
  
  encoding <- get.encoding(encoding, x)
  if (!is.data.frame(x)) 
    stop("Parameter needs to be a data frame!", call. = FALSE)
  df.var <- sjlabelled::get_label(x)
  df.val <- sjlabelled::get_labels(x)
  colcnt <- ncol(x)
  id <- seq_len(colcnt)
  if (sort.by.name) 
    id <- id[order(colnames(x))]
  tag.table <- "table"
  tag.thead <- "thead"
  tag.tdata <- "tdata"
  tag.arc <- "arc"
  tag.caption <- "caption"
  tag.omit <- "omit"
  css.table <- "border-collapse:collapse; border:none;"
  css.thead <- "border-bottom:double; font-style:italic; font-weight:normal; padding:0.2cm; text-align:left; vertical-align:top;"
  css.tdata <- "padding:0.2cm; text-align:left; vertical-align:top;"
  css.arc <- "background-color:#eeeeee"
  css.caption <- "font-weight: bold; text-align:left;"
  css.omit <- "color:#999999;"
  if (!is.null(CSS)) {
    if (!is.null(CSS[["css.table"]])) 
      css.table <- ifelse(substring(CSS[["css.table"]], 
        1, 1) == "+", paste0(css.table, substring(CSS[["css.table"]], 
        2)), CSS[["css.table"]])
    if (!is.null(CSS[["css.thead"]])) 
      css.thead <- ifelse(substring(CSS[["css.thead"]], 
        1, 1) == "+", paste0(css.thead, substring(CSS[["css.thead"]], 
        2)), CSS[["css.thead"]])
    if (!is.null(CSS[["css.tdata"]])) 
      css.tdata <- ifelse(substring(CSS[["css.tdata"]], 
        1, 1) == "+", paste0(css.tdata, substring(CSS[["css.tdata"]], 
        2)), CSS[["css.tdata"]])
    if (!is.null(CSS[["css.arc"]])) 
      css.arc <- ifelse(substring(CSS[["css.arc"]], 1, 
        1) == "+", paste0(css.arc, substring(CSS[["css.arc"]], 
        2)), CSS[["css.arc"]])
    if (!is.null(CSS[["css.caption"]])) 
      css.caption <- ifelse(substring(CSS[["css.caption"]], 
        1, 1) == "+", paste0(css.caption, substring(CSS[["css.caption"]], 
        2)), CSS[["css.caption"]])
    if (!is.null(CSS[["css.omit"]])) 
      css.omit <- ifelse(substring(CSS[["css.omit"]], 
        1, 1) == "+", paste0(css.omit, substring(CSS[["css.omit"]], 
        2)), CSS[["css.omit"]])
  }
  page.style <- sprintf("<style>\nhtml, body { background-color: white; }\n%s { %s }\n.%s { %s }\n.%s { %s }\n.%s { %s }\n%s { %s }\n.%s { %s }\n</style>", 
    tag.table, css.table, tag.thead, css.thead, tag.tdata, 
    css.tdata, tag.arc, css.arc, tag.caption, css.caption, 
    tag.omit, css.omit)
  toWrite <- sprintf("<html>\n<head>\n<meta http-equiv=\"Content-type\" content=\"text/html;charset=%s\">\n%s\n</head>\n<body>\n", 
    encoding, page.style)
  page.content <- sprintf("<table>\n  <caption>Data frame: %s</caption>\n", 
    deparse(substitute(x)))
  page.content <- paste0(page.content, "  <tr>\n    ")
  if (show.id) 
    page.content <- paste0(page.content, "<th class=\"thead\">ID</th>")
  page.content <- paste0(page.content, "<th class=\"thead\">Name</th>")
  if (show.type) 
    page.content <- paste0(page.content, "<th class=\"thead\">Type</th>")
  page.content <- paste0(page.content, "<th class=\"thead\">Label</th>")
  if (show.na) 
    page.content <- paste0(page.content, "<th class=\"thead\">missings</th>")
  if (show.values) 
    page.content <- paste0(page.content, "<th class=\"thead\">Values</th>")
  if (show.labels) 
    page.content <- paste0(page.content, "<th class=\"thead\">Value Labels</th>")
  if (show.frq) 
    page.content <- paste0(page.content, "<th class=\"thead\">Freq.</th>")
  if (show.prc) 
    page.content <- paste0(page.content, "<th class=\"thead\">%</th>")
  if (show.wtd.frq) 
    page.content <- paste0(page.content, "<th class=\"thead\">weighted Freq.</th>")
  if (show.wtd.prc) 
    page.content <- paste0(page.content, "<th class=\"thead\">weighted %</th>")
  page.content <- paste0(page.content, "\n  </tr>\n")
  if (!hide.progress) 
    pb <- utils::txtProgressBar(min = 0, max = colcnt, style = 3)
  for (ccnt in seq_len(colcnt)) {
    index <- id[ccnt]
    arcstring <- ""
    if (altr.row.col) 
      arcstring <- ifelse(sjmisc::is_even(ccnt), " arc", 
        "")
    page.content <- paste0(page.content, "  <tr>\n")
    if (show.id) 
      page.content <- paste0(page.content, sprintf("    <td class=\"tdata%s\">%i</td>\n", 
        arcstring, index))
    if (!is.list(x[[index]]) && !is.null(sjlabelled::get_note(x[[index]]))) 
      td.title.tag <- sprintf(" title=\"%s\"", sjlabelled::get_note(x[[index]]))
    else td.title.tag <- ""
    page.content <- paste0(page.content, sprintf("    <td class=\"tdata%s\"%s>%s</td>\n", 
      arcstring, td.title.tag, colnames(x)[index]))
    if (show.type) {
      vartype <- sjmisc::var_type(x[[index]])
      page.content <- paste0(page.content, sprintf("    <td class=\"tdata%s\">%s</td>\n", 
        arcstring, vartype))
    }
    if (index <= length(df.var)) {
      varlab <- df.var[index]
      if (!is.null(wrap.labels)) {
        varlab <- sjmisc::word_wrap(varlab, wrap.labels, 
          "<br>")
      }
    }
    else {
      varlab <- "<NA>"
    }
    page.content <- paste0(page.content, sprintf("    <td class=\"tdata%s\">%s</td>\n", 
      arcstring, varlab))
    if (show.na) {
      if (is.list(x[[index]])) {
        page.content <- paste0(page.content, sprintf("    <td class=\"tdata%s\"><span class=\"omit\">&lt;list&gt;</span></td>\n", 
          arcstring))
      }
      else {
        page.content <- paste0(page.content, sprintf("    <td class=\"tdata%s\">%i (%.2f%%)</td>\n", 
          arcstring, sum(is.na(x[[index]]), na.rm = T), 
          100 * sum(is.na(x[[index]]), na.rm = T)/nrow(x)))
      }
    }
    if (is.numeric(x[[index]]) && !has_value_labels(x[[index]])) {
      if (show.values || show.labels) {
        valstring <- paste0(sprintf("%a", range(x[[index]], 
          na.rm = T)), collapse = "-")
        if (show.values && show.labels) {
          colsp <- " colspan=\"2\""
          valstring <- paste0("<em>range: ", valstring, 
            "</em>")
        }
        else {
          colsp <- ""
        }
        page.content <- paste0(page.content, sprintf("    <td class=\"tdata%s\"%s>%s</td>\n", 
          arcstring, colsp, valstring))
      }
    }
    else {
      if (show.values) {
        valstring <- ""
        if (index <= ncol(x)) {
          if (is.list(x[[index]])) {
            valstring <- "<span class=\"omit\">&lt;list&gt;</span>"
          }
          else {
            vals <- sjlabelled::get_values(x[[index]])
            if (!is.null(vals)) {
              loop <- na.omit(seq_len(length(vals))[1:max.len])
              for (i in loop) {
                valstring <- paste0(valstring, vals[i])
                if (i < length(vals)) 
                  valstring <- paste0(valstring, "<br>")
              }
              if (max.len < length(vals)) 
                valstring <- paste0(valstring, "<span class=\"omit\">&lt;...&gt;</span>")
            }
          }
        }
        else {
          valstring <- "<NA>"
        }
        page.content <- paste0(page.content, sprintf("    <td class=\"tdata%s\">%s</td>\n", 
          arcstring, valstring))
      }
      if (show.labels) {
        valstring <- ""
        if (index <= length(df.val)) {
          if (is.list(x[[index]])) {
            valstring <- "<span class=\"omit\">&lt;list&gt;</span>"
          }
          else {
            vals <- df.val[[index]]
            if (!is.null(vals)) 
              vals <- na.omit(vals)
            if (is.character(x[[index]]) && !is.null(vals) && 
              !sjmisc::is_empty(vals)) {
              if (show.string.values) 
                vals <- sort(vals)
              else vals <- "<span class=\"omit\" title =\"'show.string.values = TRUE' to show values.\">&lt;output omitted&gt;</span>"
            }
            if (!is.null(vals)) {
              loop <- na.omit(seq_len(length(vals))[1:max.len])
              for (i in loop) {
                valstring <- paste0(valstring, vals[i])
                if (i < length(vals)) 
                  valstring <- paste0(valstring, "<br>")
              }
              if (max.len < length(vals)) 
                valstring <- paste0(valstring, "<span class=\"omit\">&lt;... truncated&gt;</span>")
            }
          }
        }
        else {
          valstring <- "<NA>"
        }
        page.content <- paste0(page.content, sprintf("    <td class=\"tdata%s\">%s</td>\n", 
          arcstring, valstring))
      }
    }
    if (show.frq) {
      if (is.list(x[[index]])) 
        valstring <- "<span class=\"omit\">&lt;list&gt;</span>"
      else valstring <- frq.value(index, x, df.val)
      page.content <- paste0(page.content, sprintf("    <td class=\"tdata%s\">%s</td>\n", 
        arcstring, valstring))
    }
    if (show.prc) {
      if (is.list(x[[index]])) 
        valstring <- "<span class=\"omit\">&lt;list&gt;</span>"
      else valstring <- prc.value(index, x, df.val)
      page.content <- paste0(page.content, sprintf("    <td class=\"tdata%s\">%s</td>\n", 
        arcstring, valstring))
    }
    if (show.wtd.frq && !is.null(weight.by)) {
      if (is.list(x[[index]])) 
        valstring <- "<span class=\"omit\">&lt;list&gt;</span>"
      else valstring <- frq.value(index, x, df.val, weight.by)
      page.content <- paste0(page.content, sprintf("    <td class=\"tdata%s\">%s</td>\n", 
        arcstring, valstring))
    }
    if (show.prc && !is.null(weight.by)) {
      if (is.list(x[[index]])) 
        valstring <- "<span class=\"omit\">&lt;list&gt;</span>"
      else valstring <- prc.value(index, x, df.val, weight.by)
      page.content <- paste0(page.content, sprintf("    <td class=\"tdata%s\">%s</td>\n", 
        arcstring, valstring))
    }
    if (!hide.progress) 
      utils::setTxtProgressBar(pb, ccnt)
    page.content <- paste0(page.content, "  </tr>\n")
  }
  if (!hide.progress) 
    close(pb)
  page.content <- paste(page.content, "</table>", sep = "\n")
  toWrite <- paste0(toWrite, sprintf("%s\n</body></html>", 
    page.content))
  knitr <- page.content
  knitr <- gsub("class=", "style=", knitr, fixed = TRUE, useBytes = TRUE)
  knitr <- gsub("<table", sprintf("<table style=\"%s\"", css.table), 
    knitr, fixed = TRUE, useBytes = TRUE)
  knitr <- gsub(tag.tdata, css.tdata, knitr, fixed = TRUE, 
    useBytes = TRUE)
  knitr <- gsub(tag.thead, css.thead, knitr, fixed = TRUE, 
    useBytes = TRUE)
  knitr <- gsub(tag.arc, css.arc, knitr, fixed = TRUE, useBytes = TRUE)
  if (remove.spaces) {
    knitr <- sju.rmspc(knitr)
    toWrite <- sju.rmspc(toWrite)
    page.content <- sju.rmspc(page.content)
  }
  structure(class = c("sjTable", "view_df"), list(page.style = page.style, 
    page.content = page.content, output.complete = toWrite, 
    header = NULL, knitr = knitr, file = file, show = !no.output, 
    use.viewer = use.viewer))
}

view_df2(arab4, hide.progress = T)